ArticleFrontiers in dental medicine2022
Quantitative bone imaging biomarkers and joint space analysis of the articular Fossa in temporomandibular joint osteoarthritis using artificial intelligence models.
Article in Frontiers in dental medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Comparing Traditional Versus AI-Assisted TMJ Disorder Management Approaches: A Systematic Review and Meta-Analysis.Clinical and experimental dental research · 2026Pooled it
- Application of artificial intelligence in the diagnosis and management of temporomandibular joint osteoarthritis using cone-beam computed tomography: An evidence-based systematic review.Imaging science in dentistry · 2025Review
- Relationship between temporomandibular joint space and articular disc displacement.BMC oral health · 2025Article
- Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making.Diagnostics (Basel, Switzerland) · 2024Review
- A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Perspective: Advancing the science regarding temporomandibular disorders.Frontiers in dental medicine · 2024Article
- Magnetic Resonance Imaging for Temporomandibular Joint Internal Derangement and Osteoarthritis - A Prospective Study.Annals of maxillofacial surgeryArticle
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
Abstract
Temporomandibular joint osteoarthritis (TMJ OA) is a disease with a multifactorial etiology, involving many pathophysiological processes, and requiring comprehensive assessments to characterize progressive cartilage degradation, subchondral bone remodeling, and chronic pain. This study aimed to integrate quantitative biomarkers of bone texture and morphometry of the articular fossa and joint space to advance the role of imaging phenotypes for diagnosis of Temporomandibular Joint Osteoarthritis (TMJ OA) in early to moderate stages by improving the performance of machine-learning algorithms to detect TMJ OA status. Ninety-two patients were prospectively enrolled (184 h-CBCT scans of the right and left mandibular condyles), divided into two groups: 46 control and 46 TMJ OA subjects. No significant difference in the articular fossa radiomic biomarkers was found between TMJ OA and control patients. The superior condyle-to-fossa distance (
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Registered trials
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